Prioritizing ranges to rebuild based on namespace health

ABSTRACT

A computing device includes an interface configured to interface and communicate with a dispersed storage network (DSN), a memory that stores operational instructions, and processing circuitry operably coupled to the interface and to the memory. The processing circuitry is configured to execute the operational instructions to perform various operations and functions. The computing device detects memory error(s) associated with memory device(s) of set(s) of storage units (SUs). The computing device processes the memory error(s) to generate a rebuilding priority level for at least some EDS(s) and establishes an EDS scanning rate. The computing device scans the EDS(s) based on the EDS scanning rate. When an EDS error is detected, the computing device updates the rebuilding priority level to generate an updated rebuilding priority level for the at least some of the set of EDSs and facilitates generation at least one rebuilt EDS for the EDS error based on the updated rebuilding priority level.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility patent applicationSer. No. 15/840,397, entitled “PRIORITIZING RANGES TO REBUILD BASED ONNAMESPACE HEALTH,” filed Dec. 13, 2017, pending, which claims prioritypursuant to 35 U.S.C. § 120 as a continuation-in-part (CIP) of U.S.Utility patent application Ser. No. 15/839,814, entitled “PRIORITIZINGREAD LOCATIONS BASED ON AN ERROR HISTORY,” filed Dec. 12, 2017, issuedas U.S. Pat. No. 10,051,057 on Aug. 14, 2018, which claims prioritypursuant to 35 U.S.C. § 120 as a continuation-in-part (CIP), of U.S.Utility patent application Ser. No. 15/673,978, entitled “STORING DATAIN A DISPERSED STORAGE NETWORK,” filed Aug. 10, 2017, issued as U.S.Pat. No. 10,015,255 on Jul. 3, 2018, which claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.14/876,154, entitled “STORING DATA IN A DISPERSED STORAGE NETWORK,”filed Oct. 6, 2015, issued as U.S. Pat. No. 9,774,684 on Sep. 26, 2017,which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. ProvisionalApplication No. 62/086,611, entitled “MAINTAINING DATA INTEGRITY IN ADISPERSED STORAGE NETWORK” filed Dec. 2, 2014, all of which are herebyincorporated herein by reference in their entirety and made part of thepresent U.S. Utility Patent Application for all purposes.

U.S. Utility application Ser. No. 14/876,154 also claims prioritypursuant to 35 U.S.C. § 120 as a continuation-in-part (CIP) of U.S.Utility application Ser. No. 14/792,577, entitled “DISPERSED STORAGEWRITE PROCESS,” filed Jul. 6, 2015, issued as U.S. Pat. No. 9,354,974 onMay 31, 2016, which is a continuation of U.S. Utility application Ser.No. 13/863,475, entitled “DISPERSED STORAGE WRITE PROCESS,” filed Apr.16, 2013, issued as U.S. Pat. No. 9,092,140 on Jul. 28, 2015, which is acontinuation of U.S. Utility application Ser. No. 12/797,025, entitled“DISPERSED STORAGE WRITE PROCESS,” filed Jun. 9, 2010, issued as U.S.Pat. No. 8,595,435 on Nov. 26, 2013, which claims priority pursuant to35 U.S.C. § 119(e) to U.S. Provisional Application No. 61/230,038,entitled “DISPERSED STORAGE NETWORK VERSION SYNCHRONIZATION,” filed Jul.30, 2009, all of which are hereby incorporated herein by reference intheir entirety and made part of the present U.S. Utility PatentApplication for all purposes.

U.S. Utility application Ser. No. 13/863,475 also claims prioritypursuant to 35 U.S.C. § 120 as a continuation-in-part (CIP) patentapplication of U.S. Utility application Ser. No. 12/080,042, entitled,“REBUILDING DATA ON A DISPERSED STORAGE NETWORK,” filed Mar. 31, 2008,issued as U.S. Pat. No. 8,880,799 on Nov. 4, 2014, which is acontinuation-in-part (CIP) of U.S. Utility application Ser. No.11/973,542, entitled “ENSURING DATA INTEGRITY ON A DISPERSED STORAGEGRID,” filed Oct. 9, 2007, issued as U.S. Pat. No. 9,996,413 on Jun. 12,2018, and is a continuation-in-part (CIP) of U.S. Utility applicationSer. No. 11/403,391, entitled “SYSTEM FOR REBUILDING DISPERSED DATA,”filed Apr. 13, 2006, issued as U.S. Pat. No. 7,546,427 on Jun. 9, 2009,which is a continuation-in-part (CIP) of U.S. Utility application Ser.No. 11/241,555, entitled “SYSTEMS, METHODS, AND APPARATUS FORSUBDIVIDING DATA FOR STORAGE IN A DISPERSED DATA STORAGE GRID,” filedSep. 30, 2005, issued as U.S. Pat. No. 7,953,937 on May 31, 2011, all ofwhich are hereby incorporated herein by reference in their entirety andmade part of the present U.S. Utility Patent Application for allpurposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

Within prior art data storage systems, storage errors may occur forvarious reasons. The prior art does not provide adequate means by whichsuch storage errors may be appropriately identified, processed,corrected, and/or managed. The prior art is in need of improvement inthe manner by which such data storage systems operate.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 10 is a flowchart illustrating an example of prioritizingrebuilding of encoded data slices in accordance with the presentinvention; and

FIG. 11 is a diagram illustrating an embodiment of a method forexecution by one or more computing devices in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one 10 device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

In some examples, note that dispersed or distributed storage network(DSN) memory includes one or more of a plurality of storage units (SUs)such as SUs 36 (e.g., that may alternatively be referred to adistributed storage and/or task network (DSTN) module that includes aplurality of distributed storage and/or task (DST) execution units 36that may be located at geographically different sites (e.g., one inChicago, one in Milwaukee, etc.). Each of the SUs (e.g., alternativelyreferred to as DST execution units in some examples) is operable tostore dispersed error encoded data and/or to execute, in a distributedmanner, one or more tasks on data. The tasks may be a simple function(e.g., a mathematical function, a logic function, an identify function,a find function, a search engine function, a replace function, etc.), acomplex function (e.g., compression, human and/or computer languagetranslation, text-to-voice conversion, voice-to-text conversion, etc.),multiple simple and/or complex functions, one or more algorithms, one ormore applications, etc.

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention. This diagram includes is a schematic block diagram of anotherembodiment of a dispersed storage network that includes one or morestorage sets 1-2, the network 24 of FIG. 1, and the distributed storage(DS) client module 34 of FIG. 1 and/or computing device 16 of FIG. 1.Note that such operations, functions, etc. as described herein as beingperformed by such a DS client module 34 may alternatively be performedby computing device 16. Each storage set includes a set of storage units(SUs) 1-n. Each SU includes a plurality of memory devices, where eachmemory device is associated with a set of memory devices of the set ofSUs. Each set of memory devices is associated with a unique dispersedstorage network (DSN) address range corresponding (e.g., common for eachmemory device of the set of memory devices). For example, each SUincludes a first memory device that is associated with a first commonDSN address range, a second memory device that is associated with asecond common DSN address range, and a third memory device that isassociated with a third common DSN address range. Each SU may beimplemented utilizing the SU 36 of FIG. 1. The DSN functions toprioritize rebuilding of stored encoded data slices, where the one ormore storage sets mirror stored data when at least two storage sets areutilized.

In an example of operation of the prioritizing of the rebuilding of thestored encoded data slices, the DS client module 34 detects one or morememory errors associated with a memory device of a set of memory devicesassociated with a common DSN address range. The detecting includes atleast one of issuing a memory device information status to a SUcorresponding to the memory device and receiving a memory deviceinformation status response, where the response indicates status of thememory device (e.g., unavailable, defective, available). For example,the DS client module 34 sends, via the network 24, a memory deviceinformation status request 1 to the SU 1 and receives a memory devicestatus information response 1 indicating that memory 1_2 is associatedwith a memory error.

Having detected the memory error, the DS client module 34 establishes arebuilding priority level for slice errors associated with the set ofmemory devices based on a number of detected memory errors. For example,the DS client module 34 establishes a relatively high rebuildingpriority level for the second set of memory devices when determiningthat memory devices 1_2 and 2_2 are associated with the memory errors.

Having established the rebuilding priority level for slice errors, theDS client module 34 facilitates, in accordance with the establishedrebuilding priority level, a slice error detection for stored datawithin a plurality of sets of memory devices that includes the set ofmemory devices based on detection of one or more memory errors. Forexample, the DS client module 34 establishes a slice error scanning ratefor stored data within the set of memory devices associated with the oneor more memory errors based on the one or more memory errors. Forinstance, the DS client module 34 establishes the slice error scanningrate to scan at an above average rate when more memory errors have beendetected. As another example, the DS client module 34, receives sliceinformation from the set of SUs with regards to slice errors thatindicates a slice error (e.g., a missing slice, a corrupted slice) hasbeen detected within memory device 3_2 of the second set of memorydevices.

When detecting a slice error, the DS client module 34 updates therebuilding priority level to produce an updated rebuilding prioritylevel based on one or more of a number of detected slice errors of theset of memory devices and a number of detected slice errors of acorresponding set of memory devices of another storage set (e.g., wheredata is neared, obtain memory device information in slice information).

Having updated the rebuilding priority level, the DS client module 34facilitates generating a rebuilt encoded data slice for the slice errorin accordance with the updated rebuilding priority level. For example,the DS client module 34 prioritizes rebuilding data associated with ahighest number of slice errors and memory errors first. For instance,the DS client module 34 prioritizes rebuilding data of the second set ofmemory devices over that of the third set of memory devices when threetotal errors have been detected with regards to the second set of memorydevices and just one error has been detected with regards to the thirdset of memory devices.

In an example of operation and implementation, a computing deviceincludes an interface configured to interface and communicate with adispersed or distributed storage network (DSN), a memory that storesoperational instructions, and a processing module, processor, and/orprocessing circuitry operably coupled to the interface and memory. Theprocessing module, processor, and/or processing circuitry is configuredto execute the operational instructions to perform various operations,functions, etc. In some examples, the processing module, processor,and/or processing circuitry, when operable within the computing devicebased on the operational instructions, is configured to perform variousoperations, functions, etc. In certain examples, the processing module,processor, and/or processing circuitry, when operable within thecomputing device is configured to perform one or more functions that mayinclude generation of one or more signals, processing of one or moresignals, receiving of one or more signals, transmission of one or moresignals, interpreting of one or more signals, etc. and/or any otheroperations as described herein and/or their equivalents.

In an example of operation and implementation, a computing device (e.g.,the computing device 16 such as with respect to FIG. 1, FIG. 9, and/orany other diagram, example, embodiment, etc. herein) is configured todetect one or more memory errors associated with one or more memorydevices of one or more sets of storage units (SUs) within the DSN thatdistributedly store a set of encoded data slices (EDSs). Also, a dataobject is segmented into a plurality of data segments, and a datasegment of the plurality of data segments is dispersed error encoded inaccordance with dispersed error encoding parameters to produce the setof encoded data slices (EDSs).

The computing device is also configured to process the one or morememory errors to generate a rebuilding priority level for at least someof the set of EDSs and to establish an EDS scanning rate for the set ofEDSs. The computing device is also configured to scan the set of EDSsbased on the EDS scanning rate.

When, when an EDS error is detected based on scanning of the set of EDSsbased on the EDS scanning rate, the computing device is also configuredto update the rebuilding priority level to generate an updatedrebuilding priority level for the at least some of the set of EDSs. Thecomputing device is also configured to facilitate generation at leastone rebuilt EDS for the EDS error based on the updated rebuildingpriority level.

In some examples, the computing device is also configured to detect theone or more memory errors based on issuing a memory device informationstatus to a SU corresponding to a memory device of the one or morememory devices of the one or more sets of SUs and/or receiving a memorydevice information status response from the SU corresponding to thememory device of the one or more memory devices of the one or more setsof SUs.

In even other examples, the computing device is also configured toprocess the one or more memory errors to generate a first rebuildingpriority level for a first at least one EDS of the set of EDSsassociated with a first set of SUs of the one or more sets of SUs thatis greater than a second rebuilding priority level for a second at leastone EDS of the set of EDSs associated with the first set of SUs or asecond set of SUs of the one or more sets of SUs.

In yet other examples, the computing device is also configured toprioritize rebuilding of a first at least one EDS of the set of EDSsassociated with a first set of SUs of the one or more sets of SUs overrebuilding of a second at least one EDS of the set of EDSs associatedwith the first set of SUs or a second set of SUs of the one or more setsof SUs.

In some examples, with respect to a data object, the data object issegmented into a plurality of data segments, and a data segment of theplurality of data segments is dispersed error encoded in accordance withdispersed error encoding parameters to produce a set of encoded dataslices (EDSs) (e.g., in some instances, the set of EDSs aredistributedly stored in a plurality of storage units (SUs) within theDSN). In some examples, the set of EDSs is of pillar width. Also, withrespect to certain implementations, note that the decode thresholdnumber of EDSs are needed to recover the data segment, and a readthreshold number of EDSs provides for reconstruction of the datasegment. Also, a write threshold number of EDSs provides for asuccessful transfer of the set of EDSs from a first at least onelocation in the DSN to a second at least one location in the DSN. Theset of EDSs is of pillar width and includes a pillar number of EDSs.Also, in some examples, each of the decode threshold, the readthreshold, and the write threshold is less than the pillar number. Also,in some particular examples, the write threshold number is greater thanor equal to the read threshold number that is greater than or equal tothe decode threshold number.

Note that the computing device as described herein may be located at afirst premises that is remotely located from a second premisesassociated with at least one other SU, dispersed storage (DS) unit,computing device, at least one SU of a plurality of SUs within the DSN(e.g., such as a plurality of SUs that are implemented to storedistributedly a set of EDSs), etc. In addition, note that such acomputing device as described herein may be implemented as any of anumber of different devices including a managing unit that is remotelylocated from another SU, DS unit, computing device, etc. within the DSNand/or other device within the DSN, an integrity processing unit that isremotely located from another computing device and/or other devicewithin the DSN, a scheduling unit that is remotely located from anothercomputing device and/or SU within the DSN, and/or other device. Also,note that such a computing device as described herein may be of any of avariety of types of devices as described herein and/or their equivalentsincluding a DS unit and/or SU included within any group and/or set of DSunits and/or SUs within the DSN, a wireless smart phone, a laptop, atablet, a personal computers (PC), a work station, and/or a video gamedevice, and/or any type of computing device or communication device.Also, note also that the DSN may be implemented to include and/or bebased on any of a number of different types of communication systemsincluding a wireless communication system, a wire lined communicationsystem, a non-public intranet system, a public internet system, a localarea network (LAN), and/or a wide area network (WAN). Also, in someexamples, any device configured to support communications within such aDSN may be also be configured to and/or specifically implemented tosupport communications within a satellite communication system, awireless communication system, a wired communication system, afiber-optic communication system, and/or a mobile communication system(and/or any other type of communication system implemented using anytype of communication medium or media).

FIG. 10 is a flowchart illustrating an example of prioritizingrebuilding of encoded data slices in accordance with the presentinvention. This diagram includes is a flowchart illustrating an exampleof prioritizing rebuilding of encoded data slices. The method 1000begins or continues at a step 1010 where a processing module (e.g., of adistributed storage (DS) and/or client module and/or computing device)detects one or more memory errors associated with one or more memorydevices of a set of memory devices. The detecting includes at least oneof interpreting an error message, initiating a query, and interpreting aquery response.

The method 1000 continues at the step 1020 where the processing moduleestablishes a rebuilding priority level for slice errors associated withthe set of memory devices based on the detected memory errors. Forexample, the processing module establishes a higher priority level whendetecting more memory errors for the set of memory devices.

The method 1000 continues at the step 1030 where the processing modulefacilitates, in accordance with the rebuilding priority level, a sliceerror detection for storage in a plurality of sets of memory devicesthat includes the set of memory devices. For example, the processingmodule facilitates in accordance with other rebuilding priority levelsassociated with other sets of memory devices of the plurality of sets ofmemory devices and with the rebuilding priority level of the set ofmemory devices. For instance, the processing module scans more often forslice errors within available memory devices associated with othermemory devices corresponding to hire numbers of memory errors.

When detecting a slice error, the method 1000 continues at the step 1040where the processing module updates the rebuilding priority level toproduce an updated rebuilding priority level. For example, theprocessing module utilizes a total number of errors based on memoryerrors and slice errors to update the rebuilding priority level.

The method 1000 continues at the step 1050 where the processing modulefacilitates generating a rebuilt encoded data slice for the detectedslice error in accordance with the updated rebuilding priority level.For example, the processing module facilitates the generating of therebuilt encoded data slice in accordance with one or more of the otherrebuilding priority levels associated with other sets of memory devicesof the plurality of sets of memory devices, with the rebuilding prioritylevel of the set of memory devices, and with a rebuilding priority levelof an associated set of memory devices of another set of memory devices(e.g., a mirror set of memory devices).

FIG. 11 is a diagram illustrating an embodiment of a method forexecution by one or more computing devices in accordance with thepresent invention. The method 1100 operates in step 1110 by detectingone or more memory errors associated with one or more memory devices ofone or more sets of storage units (SUs) within a dispersed ordistributed storage network (DSN) that distributedly store a set ofencoded data slices (EDSs), wherein a data object is segmented into aplurality of data segments, wherein a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce the set of encoded data slices(EDSs).

The method 1100 then continues in step 1120 by processing the one ormore memory errors to generate a rebuilding priority level for at leastsome of the set of EDSs. The method 1100 operates in step 1130 byestablishing an EDS scanning rate for the set of EDSs. The method 1100then continues in step 1140 by scanning the set of EDSs based on the EDSscanning rate.

When no EDS error is detected based on scanning of the set of EDSs basedon the EDS scanning rate (block 1142), the method 1100 ends (oralternatively performs one or more other operations that may includelooping back to one of the operations in the method 1100). When an EDSerror is detected based on scanning of the set of EDSs based on the EDSscanning rate (block 1142), the method 1100 then operates in step 1150by updating the rebuilding priority level to generate an updatedrebuilding priority level for the at least some of the set of EDSs andin step 1160 by facilitating (e.g., via an interface of the computingdevice that is configured to interface and communicate with a dispersedor distributed storage network (DSN)) generation of at least one rebuiltEDS for the EDS error based on the updated rebuilding priority level.

This disclosure presents, among other things, various novel solutionsthat operate to perform prioritizing memory devices to replace based onnamespace health. For example, when the namespace ranges assigned tomemory devices is known, and the failed/recovered state of each memorydevice is known, then a namespace health map can be generated asfollows: Initialize entire namespace range from first name to last namewith a value equal to the width; and then, for each memory device (orSU) that has failed but not yet been rebuilt, decrement the valueassociated with the namespace range for which that memory device (or SU)is responsible for by 1.

In some examples, this results in a complete picture of how many slicesare expected to be available and how many are expected to be missing forany particular name within the namespace, it also enables a list of“least healthy ranges” to be generated which correspond to thoseoverlapping ranges that include the greatest number of unrecoveredfailures. Since these least healthy ranges correspond to data at thehighest risk of being lost, rebuild modules may prioritize thescanning/rebuilding activity for data within these ranges.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A computing device comprising: an interfaceconfigured to interface and communicate with a dispersed or distributedstorage network (DSN); memory that stores operational instructions; andprocessing circuitry operably coupled to the interface and to thememory, wherein the processing circuitry is configured to execute theoperational instructions to: detect one or more memory errors associatedwith one or more memory devices of one or more sets of storage units(SUs) within the DSN that distributedly store a set of encoded dataslices (EDSs), wherein a data object is segmented into a plurality ofdata segments, wherein a data segment of the plurality of data segmentsis dispersed error encoded in accordance with dispersed error encodingparameters to produce the set of encoded data slices (EDSs); process theone or more memory errors to generate a rebuilding priority level for atleast some of the set of EDSs; based on an EDS error that is detectedbased on scanning of the set of EDSs: update the rebuilding prioritylevel to generate an updated rebuilding priority level for the at leastsome of the set of EDSs; and facilitate generation of at least onerebuilt EDS for the EDS error based on the updated rebuilding prioritylevel.
 2. The computing device of claim 1, wherein the processingcircuitry is further configured to execute the operational instructionsto: establish an EDS scanning rate for the set of EDSs; and scan the setof EDSs based on the EDS scanning rate to determine whether the set ofEDSs includes the EDS error.
 3. The computing device of claim 2, whereinthe processing circuitry is further configured to execute theoperational instructions to: based on the EDS error that is detectedbased on scanning of the set of EDSs based on the EDS scanning rate:update the rebuilding priority level to generate the updated rebuildingpriority level for the at least some of the set of EDSs; and facilitategeneration of at least one rebuilt EDS for the EDS error based on theupdated rebuilding priority level.
 4. The computing device of claim 1,wherein the processing circuitry is further configured to execute theoperational instructions to: detect the one or more memory errors basedon at least one of issuing a memory device information status to a SUcorresponding to a memory device of the one or more memory devices ofthe one or more sets of SUs or receiving a memory device informationstatus response from the SU corresponding to the memory device of theone or more memory devices of the one or more sets of SUs.
 5. Thecomputing device of claim 1, wherein the processing circuitry is furtherconfigured to execute the operational instructions to: process the oneor more memory errors to generate a first rebuilding priority level fora first at least one EDS of the set of EDSs associated with a first setof SUs of the one or more sets of SUs that is greater than a secondrebuilding priority level for a second at least one EDS of the set ofEDSs associated with the first set of SUs or a second set of SUs of theone or more sets of SUs.
 6. The computing device of claim 1, wherein theprocessing circuitry is further configured to execute the operationalinstructions to: prioritize rebuilding of a first at least one EDS ofthe set of EDSs associated with a first set of SUs of the one or moresets of SUs over rebuilding of a second at least one EDS of the set ofEDSs associated with the first set of SUs or a second set of SUs of theone or more sets of SUs.
 7. The computing device of claim 1, wherein: adecode threshold number of EDSs are needed to recover the data segment;a read threshold number of EDSs provides for reconstruction of the datasegment; a write threshold number of EDSs provides for a successfultransfer of the set of EDSs from a first at least one location in theDSN to a second at least one location in the DSN; the set of EDSs is ofpillar width and includes a pillar number of EDSs; each of the decodethreshold number, the read threshold number, and the write thresholdnumber is less than the pillar number; and the write threshold number isgreater than or equal to the read threshold number that is greater thanor equal to the decode threshold number.
 8. The computing device ofclaim 1, wherein the computing device is located at a first premisesthat is remotely located from a second premises of at least one SU ofthe one or more sets of SUs within the DSN.
 9. The computing device ofclaim 1 further comprising: a SU of the one or more sets of SUs withinthe DSN, a wireless smart phone, a laptop, a tablet, a personalcomputers (PC), a work station, or a video game device.
 10. Thecomputing device of claim 1, wherein the DSN includes at least one of awireless communication system, a wire lined communication system, anon-public intranet system, a public internet system, a local areanetwork (LAN), or a wide area network (WAN).
 11. A method for executionby a computing device, the method comprising: detecting one or morememory errors associated with one or more memory devices of one or moresets of storage units (SUs) within a dispersed or distributed storagenetwork (DSN that distributedly store a set of encoded data slices(EDSs), wherein a data object is segmented into a plurality of datasegments, wherein a data segment of the plurality of data segments isdispersed error encoded in accordance with dispersed error encodingparameters to produce the set of encoded data slices (EDSs); processingthe one or more memory errors to generate a rebuilding priority levelfor at least some of the set of EDSs; and based on an EDS error that isdetected based on scanning of the set of EDSs: updating the rebuildingpriority level to generate an updated rebuilding priority level for theat least some of the set of EDSs; and facilitating, via an interface ofthe computing device configured to interface and communicate with theDSN, generation of at least one rebuilt EDS for the EDS error based onthe updated rebuilding priority level.
 12. The method of claim 11further comprising: establishing an EDS scanning rate for the set ofEDSs; and scanning the set of EDSs based on the EDS scanning rate todetermine whether the set of EDSs includes the EDS error.
 13. The methodof claim 12, further comprising: based on the EDS error that is detectedbased on scanning of the set of EDSs based on the EDS scanning rate:updating the rebuilding priority level to generate the updatedrebuilding priority level for the at least some of the set of EDSs; andfacilitating, via the interface, generation of at least one rebuilt EDSfor the EDS error based on the updated rebuilding priority level. 14.The method of claim 11 further comprising: detecting the one or morememory errors based on at least one of issuing a memory deviceinformation status to a SU corresponding to a memory device of the oneor more memory devices of the one or more sets of SUs or receiving amemory device information status response from the SU corresponding tothe memory device of the one or more memory devices of the one or moresets of SUs.
 15. The method of claim 11 further comprising: processingthe one or more memory errors to generate a first rebuilding prioritylevel for a first at least one EDS of the set of EDSs associated with afirst set of SUs of the one or more sets of SUs that is greater than asecond rebuilding priority level for a second at least one EDS of theset of EDSs associated with the first set of SUs or a second set of SUsof the one or more sets of SUs.
 16. The method of claim 11 furthercomprising: prioritizing rebuilding of a first at least one EDS of theset of EDSs associated with a first set of SUs of the one or more setsof SUs over rebuilding of a second at least one EDS of the set of EDSsassociated with the first set of SUs or a second set of SUs of the oneor more sets of SUs.
 17. The method of claim 11, wherein: a decodethreshold number of EDSs are needed to recover the data segment; a readthreshold number of EDSs provides for reconstruction of the datasegment; a write threshold number of EDSs provides for a successfultransfer of the set of EDSs from a first at least one location in theDSN to a second at least one location in the DSN; the set of EDSs is ofpillar width and includes a pillar number of EDSs; each of the decodethreshold number, the read threshold number, and the write thresholdnumber is less than the pillar number; and the write threshold number isgreater than or equal to the read threshold number that is greater thanor equal to the decode threshold number.
 18. The method of claim 11,wherein the computing device is located at a first premises that isremotely located from a second premises of at least one SU of the one ormore sets of SUs within the DSN.
 19. The method of claim 11, wherein thecomputing device includes a SU of the one or more sets of SUs within theDSN, a wireless smart phone, a laptop, a tablet, a personal computers(PC), a work station, or a video game device.
 20. The method of claim11, wherein the DSN includes at least one of a wireless communicationsystem, a wire lined communication system, a non-public intranet system,a public internet system, a local area network (LAN), or a wide areanetwork (WAN).